Modelling of emerging threates and epidemics

Sebastian Funk

https://epiforecasts.io

Models are a tool to combine data (what we know) with assumptions and theory (what we think) to learn about what we don’t know.

January 2020: Can COVID-19 be controlled by contact tracing?

Hellewell et al., Lancet Glob Health, 2020

Probability of control depends on intensity of transmission and contact tracing effort.

Hellewell et al., Lancet Glob Health, 2020

We illustrate the potential impact that flawed model inferences can have on public health policy with the model described […] by Joel Hellewell and colleagues, which is part of the scientific evidence informing the UK Government’s response to COVID-19.

Gudrasani & Ziauddeen, Lancet Glob Health, 2020

“All models are wrong, but some are useful”

George Box

“All models are wrong, but some are useful

  • wrong: how wrong?
  • some: which ones?

How wrong are models?

Evaluation of forecasts

Assess quality of models by how closely prediction matches reality

Types of predictive modelling

Forecasts vs. Scenarios

Image from: https://covid19scenariomodelinghub.org/

Forecast hubs support systematic collection of forecasts

Reich et al., Am J Public Health, 2022

Median ensemble outperformed individual models

Sherratt et al., eLife, 2023

Case forecasts difficult from a few weeks from the forecast date

Sherratt et al., eLife, 2023

Humans were better than models at predicting cases, but not deaths

Bosse et al., PLOS Comp Biol, 2022

No clear pattern of which type of model performed best

Sherratt et al., 2025

Not all modelling is forecasting, can we evaluate other models?

Any model of the future is a prediction and can be evaluated as such.

Howerton et al., Nat Comm, 2023

Which models are useful?

Utility could be independent of predictive ability

Saltelli, 2018

Utility is not being assessed by modellers

Collaboration with Robert Koch Institute / WHO.

Outlook: how can we improve modelling in future epidemics

Predictable tasks during epidemics

Figure courtesy of Adam Kucharski

Predictable task: mpox nowcasting

UKHSA, 2022
Overton et al. /PLOS Comp Biol/, 2023

Unpredictable task: the impact of the transmission network

Endo et al. /Science/, 2022

Supporting predictable modelling with software tools

Summary / discussion points

  • Initial work during COVID-19 was strongly driven by available models and data. Future work can be facilitated by R packages etc. that serve as tools for predictable tasks.
  • Multi-model efforts have created insights into the accuracy of models for prediction.
  • More work is needed to determine which data and methods for forecasting best support public health.
  • Efforts are ongoing to assess the usefulness of modelling efforts.

Thank you

Slides at

https://epiforecasts.io/slides/rki_20250519.html